---
res:
  bibo_abstract:
  - "We prove that the mesoscopic linear statistics ∑if(na(σi−z0)) of the eigenvalues
    {σi}i of large n×n non-Hermitian random matrices with complex centred i.i.d. entries
    are asymptotically Gaussian for any H20-functions f around any point z0 in the
    bulk of the spectrum on any mesoscopic scale 0<a<1/2. This extends our previous
    result (Cipolloni et al. in Commun Pure Appl Math, 2019. arXiv:1912.04100), that
    was valid on the macroscopic scale, a=0\r\n, to cover the entire mesoscopic regime.
    The main novelty is a local law for the product of resolvents for the Hermitization
    of X at spectral parameters z1,z2 with an improved error term in the entire mesoscopic
    regime |z1−z2|≫n−1/2. The proof is dynamical; it relies on a recursive tandem
    of the characteristic flow method and the Green function comparison idea combined
    with a separation of the unstable mode of the underlying stability operator.@eng"
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Giorgio
      foaf_name: Cipolloni, Giorgio
      foaf_surname: Cipolloni
      foaf_workInfoHomepage: http://www.librecat.org/personId=42198EFA-F248-11E8-B48F-1D18A9856A87
    orcid: 0000-0002-4901-7992
  - foaf_Person:
      foaf_givenName: László
      foaf_name: Erdös, László
      foaf_surname: Erdös
      foaf_workInfoHomepage: http://www.librecat.org/personId=4DBD5372-F248-11E8-B48F-1D18A9856A87
    orcid: 0000-0001-5366-9603
  - foaf_Person:
      foaf_givenName: Dominik J
      foaf_name: Schröder, Dominik J
      foaf_surname: Schröder
      foaf_workInfoHomepage: http://www.librecat.org/personId=408ED176-F248-11E8-B48F-1D18A9856A87
    orcid: 0000-0002-2904-1856
  bibo_doi: 10.1007/s00440-023-01229-1
  bibo_volume: 188
  dct_date: 2024^xs_gYear
  dct_identifier:
  - UT:001118972500001
  dct_isPartOf:
  - http://id.crossref.org/issn/0178-8051
  - http://id.crossref.org/issn/1432-2064
  dct_language: eng
  dct_publisher: Springer Nature@
  dct_title: Mesoscopic central limit theorem for non-Hermitian random matrices@
...